A challenge to the permissibility of procreation

The Non-Identity Problem (the NIP) raises a series of problems to the morality of procreation. The NIP, I believe, highlights a fundamental problem concerning the justifiability of procreation. In chapter 1, I introduce the NIP and show that the logic of the NIP does not rule out the anti-natalist claim. Moreover, there are reasons, which are independent of its capacity to solve the NIP, to accept the anti-natalist claim. However, the anti-natalist claim poses a serious justificatory challenge to the permissibility of procreation. To see whether we can restore the permissibility of procreation, I examine the impersonal pro-natalist claim in chapter 2 and argue that there is not only no good reason to believe that whatever makes life worth living gives us an impersonal reason to procreate but good reason not to believe that. In chapter 3, I examine the justifications for the right to procreate and argue that most promising ground – that is, parenting interest – fails to establish a moral right to procreate. Therefore, the justification of procreation is in trouble, at least, at the individual level because there is a reason against procreation out of concern for possible people and no impersonal reason to procreate and the moral significance of parenting interests fails to justify imposing the harm of coming into existence. This is, nevertheless, a somewhat moderate conclusion because it does not defend that procreation is all-things-considered wrong. More works need to be done to show why procreation is morally permissible (or impermissible)

Learning Multi-Level Information for Dialogue Response Selection by Highway Recurrent Transformer

With the increasing research interest in dialogue response generation, there is an emerging branch formulating this task as selecting next sentences, where given the partial dialogue contexts, the goal is to determine the most probable next sentence. Following the recent success of the Transformer model, this paper proposes (1) a new variant of attention mechanism based on multi-head attention, called highway attention, and (2) a recurrent model based on transformer and the proposed highway attention, so-called Highway Recurrent Transformer. Experiments on the response selection task in the seventh Dialog System Technology Challenge (DSTC7) show the capability of the proposed model of modeling both utterance-level and dialogue-level information; the effectiveness of each module is further analyzed as well

Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking

Action recognition has received increasing attention from the computer vision and machine learning communities in the last decade. To enable the study of this problem, there exist a vast number of action datasets, which are recorded under controlled laboratory settings, real-world surveillance environments, or crawled from the Internet. Apart from the "in-the-wild" datasets, the training and test split of conventional datasets often possess similar environments conditions, which leads to close to perfect performance on constrained datasets. In this paper, we introduce a new dataset, namely Multi-Camera Action Dataset (MCAD), which is designed to evaluate the open view classification problem under the surveillance environment. In total, MCAD contains 14,298 action samples from 18 action categories, which are performed by 20 subjects and independently recorded with 5 cameras. Inspired by the well received evaluation approach on the LFW dataset, we designed a standard evaluation protocol and benchmarked MCAD under several scenarios. The benchmark shows that while an average of 85% accuracy is achieved under the closed-view scenario, the performance suffers from a significant drop under the cross-view scenario. In the worst case scenario, the performance of 10-fold cross validation drops from 87.0% to 47.4%

Stacking sequence determines Raman intensities of observed interlayer shear modes in 2D layered materials - A general bond polarizability model

2D layered materials have recently attracted tremendous interest due to their fascinating properties and potential applications. The interlayer interactions are much weaker than the intralayer bonds, allowing the as-synthesized materials to exhibit different stacking sequences (e.g. ABAB, ABCABC), leading to different physical properties. Here, we show that regardless of the space group of the 2D material, the Raman frequencies of the interlayer shear modes observed under the typical configuration blue shift for AB stacked materials, and red shift for ABC stacked materials, as the number of layers increases. Our predictions are made using an intuitive bond polarizability model which shows that stacking sequence plays a key role in determining which interlayer shear modes lead to the largest change in polarizability (Raman intensity); the modes with the largest Raman intensity determining the frequency trends. We present direct evidence for these conclusions by studying the Raman modes in few layer graphene, MoS2, MoSe2, WSe2 and Bi2Se3, using both first principles calculations and Raman spectroscopy. This study sheds light on the influence of stacking sequence on the Raman intensities of intrinsic interlayer modes in 2D layered materials in general, and leads to a practical way of identifying the stacking sequence in these materials.Comment: 30 pages, 8 figure

利用滲透試驗探討雙層土壤之滲流沖蝕行為及其數值模擬

Seepage erosion occurs when finer particles are dragged out from other soil particles by water. This type of erosion causes progressive failure inward into the slopes and slope instabilities. Therefore, it is necessary to explore the behavior of seepage erosion in order to prevent such failure in slopes. According to results of field investigations, we do seepage erosion experiments in a laboratory to understand the erosion behavior. After that, we utilize FEM soft-ware – FLAC5.0 in order to determine the feasibility of numerical analysis in simulating seepage erosion behavior.滲流沖蝕係指土壤中的細顆粒因地下水流驅動通過較大顆粒間之孔隙，被帶離坡面後，會由坡面向坡體內部發展出漸進式破壞，進而引發邊坡問題，故對邊坡滲流沖蝕行為的瞭解有其必要性。因此，本研究根據現地調查結果，於室內利用滲透試驗儀器進行滲流沖蝕試驗，以了解不同情形下各試體之沖蝕行為。而後，為了解數值軟體用於模擬滲流沖蝕行為之可行性，故嘗試採用有限差分法軟體－FLAC5.0 進行模擬，以期能作為未來用於滲流沖蝕模擬之參考

Apical-Basal Polarity Signaling Components, Lgl1 and aPKCs, Control Glutamatergic Synapse Number and Function.

Normal synapse formation is fundamental to brain function. We show here that an apical-basal polarity (A-BP) protein, Lgl1, is present in the postsynaptic density and negatively regulates glutamatergic synapse numbers by antagonizing the atypical protein kinase Cs (aPKCs). A planar cell polarity protein, Vangl2, which inhibits synapse formation, was decreased in synaptosome fractions of cultured cortical neurons from Lgl1 knockout embryos. Conditional knockout of Lgl1 in pyramidal neurons led to reduction of AMPA/NMDA ratio and impaired plasticity. Lgl1 is frequently deleted in Smith-Magenis syndrome (SMS). Lgl1 conditional knockout led to increased locomotion, impaired novel object recognition and social interaction. Lgl1+/- animals also showed increased synapse numbers, defects in open field and social interaction, as well as stereotyped repetitive behavior. Social interaction in Lgl1+/- could be rescued by NMDA antagonists. Our findings reveal a role of apical-basal polarity proteins in glutamatergic synapse development and function and also suggest a potential treatment for SMS patients with Lgl1 deletion